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We study Anderson localization of non-interacting random hopping fermions on bipartite lattices in two dimensions, focusing our attention to strong disorder features of the model. We concentrate ourselves on specific models with a linear…

Disordered Systems and Neural Networks · Physics 2009-11-10 H. Yamada , T. Fukui

The distribution of the correlation dimension in a power law band random matrix model having critical, i.e. multifractal, eigenstates is numerically investigated. It is shown that their probability distribution function has a fixed point as…

Disordered Systems and Neural Networks · Physics 2009-11-07 I. Varga

A family of unitary $\alpha$-Ensembles of random matrices with governable confinement potential $V(x) ~ |x|^\alpha$ is studied employing exact results of the theory of non-classical orthogonal polynomials. The density of levels, two-point…

Condensed Matter · Physics 2009-10-28 V. Freilikher , E. Kanzieper , I. Yurkevich

We develop a theory for the eigenvalue density of arbitrary non-Hermitian Euclidean matrices. Closed equations for the resolvent and the eigenvector correlator are derived. The theory is applied to the random Green's matrix relevant to wave…

Disordered Systems and Neural Networks · Physics 2011-08-26 A. Goetschy , S. E. Skipetrov

The article reviews recent developments in the theory of fluctuations and correlations of energy levels and eigenfunction amplitudes in diffusive mesoscopic samples. Various spatial geometries are considered, with emphasis on…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander D. Mirlin

In this paper, we present a general framework to solve a fundamental problem in Random Matrix Theory (RMT), i.e., the problem of describing the joint distribution of eigenvalues of the sum $\bsA+\bsB$ of two independent random Hermitian…

Quantum Physics · Physics 2019-11-14 Lin Zhang , Yixin Jiang , Junde Wu

In this paper, we derive limit laws for the empirical spectral distributions of random band and block matrices with correlated entries. In the first part of the paper, we study band matrices with approximately uncorrelated entries. We…

Probability · Mathematics 2022-02-11 Riccardo Catalano , Michael Fleermann , Werner Kirsch

The paper continues the development of the rigorous supersymmetric transfer matrix approach to the random band matrices started in J Stat Phys 164:1233 -- 1260, 2016; Commun Math Phys 351:1009 -- 1044, 2017. We consider random Hermitian…

Mathematical Physics · Physics 2018-03-14 Mariya Shcherbina , Tatyana Shcherbina

We consider the eigenvalues of a fixed, non-normal matrix subject to a small additive perturbation. In particular, we consider the case when the fixed matrix is a banded Toeplitz matrix, where the bandwidth is allowed to grow slowly with…

Probability · Mathematics 2022-08-29 Sean O'Rourke , Philip Matchett Wood

We discuss the limiting spectral density of real symmetric random matrices. Other than in standard random matrix theory the upper diagonal entries are not assumed to be independent, but we will fill them with the entries of a stochastic…

Probability · Mathematics 2015-12-09 Matthias Löwe , Kristina Schubert

In this monograph, we prove an asymptotic approximation for integrals of probability densities over sets in finite dimensional euclidean space, which are far away from the origin (asymptotic sets). We use this approximation to investigate…

Probability · Mathematics 2009-09-29 Philippe Barbe

The properties of the first (largest) eigenvalue and its eigenvector (first eigenvector) are investigated for large sparse random symmetric matrices that are characterized by bimodal degree distributions. In principle, one should be able to…

Disordered Systems and Neural Networks · Physics 2012-08-03 Yoshiyuki Kabashima , Hisanao Takahashi

In this paper we consider random block matrices, which generalize the general beta ensembles, which were recently investigated by Dumitriu and Edelmann (2002, 2005). We demonstrate that the eigenvalues of these random matrices can be…

Probability · Mathematics 2008-09-29 Holger Dette , Bettina Reuther

In this paper we calculate, in the large N limit, the eigenvalue density of an infinite product of random unitary matrices, each of them generated by a random hermitian matrix. This is equivalent to solving unitary diffusion generated by a…

Mathematical Physics · Physics 2009-11-10 Romuald A. Janik , Waldemar Wieczorek

We investigate the eigenvalue density in ensembles of large sparse Bernoulli random matrices. We demonstrate that the fraction of linear subgraphs just below the percolation threshold is about 95\% of all finite subgraphs, and the…

Disordered Systems and Neural Networks · Physics 2016-01-20 V. Avetisov , P. L. Krapivsky , S. Nechaev

An exact analytical description of extreme intensity statistics in complex random states is derived. These states have the statistical properties of the Gaussian and Circular Unitary Ensemble eigenstates of random matrix theory. Although…

Quantum Physics · Physics 2011-08-02 Arul Lakshminarayan , Steven Tomsovic , Oriol Bohigas , Satya N. Majumdar

We consider 1d random Hermitian $N\times N$ block band matrices consisting of $W\times W$ random Gaussian blocks (parametrized by $j,k \in\Lambda=[1,n]\cap \mathbb{Z}$, $N=nW$) with a fixed entry's variance…

Mathematical Physics · Physics 2019-10-09 Mariya Shcherbina , Tatyana Shcherbina

We consider ensembles of $N \times N$ Hermitian Wigner matrices, whose entries are (up to the symmetry constraints) independent and identically distributed random variables. Assuming sufficient regularity for the probability density…

Mathematical Physics · Physics 2011-03-15 Anna Maltsev , Benjamin Schlein

In this paper, we investigate the asymptotic behaviors of the extreme eigenvectors in a general spiked covariance matrix, where the dimension and sample size increase proportionally. We eliminate the restrictive assumption of the block…

Statistics Theory · Mathematics 2024-05-15 Zhangni Pu , Xiaozhuo Zhang , Jiang Hu , Zhidong Bai

We propose a new randomized optimization method for high-dimensional problems which can be seen as a generalization of coordinate descent to random subspaces. We show that an adaptive sampling strategy for the random subspace significantly…

Optimization and Control · Mathematics 2019-12-19 Jonathan Lacotte , Mert Pilanci , Marco Pavone